Determining whether a candidate biometric (e.g., facial image, fingerprint, genetic sequence, iris scan, or other biometric, or a reduced-dimensionality representation thereof) exists within a list, a database, or other dataset of biometrics can be a difficult task to automate, particularly when multiple biometrics of the same person exist within the dataset of biometrics. Adding minor differences among the respective biometrics presents further difficulties. For example, it may be desirable to automate a process for determining whether a facial image (or multiple facial images) of a person taken at point of entry corresponds to one or more facial images stored in a database of persons of interest (e.g., suspects, criminals, terrorists, employees, VIPs, “whales,” etc.). In a similar vein, determining whether fraud exists in a dataset of biometrics, either as persons having multiple identities or persons posing under stolen identities, is a similarly difficult task.
What is needed is an improved system and method for detecting potential matches, and/or their relative strength, between a candidate biometric and a dataset of biometrics.